Low Back Compression Research Articles

FMS™ scores and low-back loading during lifting – Whole-body movement screening as an ergonomic tool?

BackgroundPrevious research suggests that a general whole-body movement screen could be used to identify personal movement attributes that promote potentially injurious low-back loading patterns at work. The purpose of this study was to examine the relationship between Functional Movement Screen™ (FMS) composite scores and the low-back loading response to lifting. MethodsFifteen men who scored greater than 14 on the FMS (high-scorers) and 15 height- and weight-matched low-scorers (FMS < 14) performed sagittally symmetric and asymmetric laboratory-based lifting tasks. A three-dimensional dynamic biomechanical model was used to calculate peak low-back loading levels, and the angle of the lumbar spine was captured at the instant when the peak compressive force was applied. ResultsRegardless of the lifting task performed, there were no differences in peak low-back compression (p ≥ 0.4157), anterior/posterior reaction shear (p ≥ 0.5645), or medial/lateral reaction shear (p ≥ 0.2581) forces between the high- and low-scorers. At the instant when peak compressive forces were applied, differences in the lumbar spine angle between high- and low-scores were not statistically significant about the lateral bend (p ≥ 0.4215), axial twist (p ≥ 0.2734), or flexion/extension (p ≥ 0.1354) axes, but there was a tendency for the lumbar spine to be more deviated in the low-scorers. ConclusionsUsing the previously established injury prediction threshold value of 14, the composite FMS score was not related to the peak low-back loading magnitudes in lifting. Though not statistically significant, the tendency for the lumbar spines of low-scorers to be more deviated when the peak low-back compression force was imposed could be biomechanically meaningful because spinal load tolerance varies with posture. Future attempts to modify or reinterpret FMS scoring are warranted given that several previous studies have revealed links between composite FMS scores and musculoskeletal complaints.

Effect of Mental Processing on Low Back Load While Lifting an Object

Biomechanical study using a 3D motion analysis system conducted in a laboratory setting. To determine the effect of mental processing on low back load during lifting. In addition to ergonomic factors such as frequent lifting, work-related psychosocial factors are significant in the onset of disabling back pain. Although the ergonomic effects on low back load while lifting have been investigated and are widely accepted in the workplace, few studies have investigated the effect of psychosocial factors on low back load while lifting. Thirteen healthy subjects lifted a box from the ground in 4 different lifting tasks in randomized order: (1) squat posture with knees flexed; (2) stoop posture with knees extended; (3) squat posture with mental processing using arithmetic tasks; and (4) stoop posture with mental processing using arithmetic tasks. We used a 3D motion analysis system and 4 force plates to record kinematic and kinetic data. We calculated dynamic triaxial low back joint moments and low back compression force as index parameters of low back load under these experimental conditions. Mental processing significantly increased peak low back compression force and low back extension moment, but not lateral flexion or rotation moment, while lifting in both lifting postures. Also, mental processing increased trunk bending angles in the squat posture. Although a tendency for decreased pelvic forward tilt was observed, mental processing did not significantly decrease forward pelvic tilt in the stoop posture. Mental processing during lifting tasks seems to affect both trunk and pelvis angles in the sagittal plane for squat and stoop postures, resulting in increased low back load. The present findings might help explain the effect of ergonomic demands of lifting tasks as well as psychosocial factors responsible for the onset of disabling back pain. 2.

Low back loads while walking and carrying: comparing the load carried in one hand or in both hands

This study investigates the consequences of carrying load in one hand versus both hands. Six participants walked carrying buckets containing various weights. The weight was either carried in one hand or distributed evenly between both hands. Electromyography, force plate and body kinematic data were input to a three-dimensional anatomically detailed model of the spine to calculate spine loading. Carrying loads in one hand resulted in more load on the low back than when the load was split between both hands. When carrying 30 kg in one hand, the low back compression exceeded 2800 N; however, splitting the load between hands reduced low back compression to 1570 N (reduction of 44%). Doubling the total load by carrying 30 kg in each hand actually produced lower spine compression than when carrying 30 kg in one hand. Balancing the load between both hands when carrying material has merit and should be considered when designing work. Practitioner Summary: Carrying a load in one hand (30 kg) resulted in more spine load than splitting the same load between both hands (15 kg). When carrying double the load in both hands (30 kg in each hand vs. 30 kg in one hand), spine load decreased, suggesting merit in balancing load when designing work.

Kettlebell Swing, Snatch, and Bottoms-Up Carry: Back and Hip Muscle Activation, Motion, and Low Back Loads

The intent of this study was to quantify spine loading during different kettlebell swings and carries. No previously published studies of tissue loads during kettlebell exercises could be found. Given the popularity of kettlebells, this study was designed to provide an insight into the resulting joint loads. Seven male subjects participated in this investigation. In addition, a single case study of the kettlebell swing was performed on an accomplished kettlebell master. Electromyography, ground reaction forces (GRFs), and 3D kinematic data were recorded during exercises using a 16-kg kettlebell. These variables were input into an anatomically detailed biomechanical model that used normalized muscle activation; GRF; and spine, hip, and knee motion to calculate spine compression and shear loads. It was found that kettlebell swings create a hip-hinge squat pattern characterized by rapid muscle activation-relaxation cycles of substantial magnitudes (∼50% of a maximal voluntary contraction [MVC] for the low back extensors and 80% MVC for the gluteal muscles with a 16-kg kettlebell) resulting in about 3,200 N of low back compression. Abdominal muscular pulses together with the muscle bracing associated with carries create kettlebell-specific training opportunities. Some unique loading patterns discovered during the kettlebell swing included the posterior shear of the L4 vertebra on L5, which is opposite in polarity to a traditional lift. Thus, quantitative analysis provides an insight into why many individuals credit kettlebell swings with restoring and enhancing back health and function, although a few find that they irritate tissues.

A polynomial equation to predict low back compression force: accounting for the effects of load height on instability

The purpose of this study was to develop a regression equation that, incorporating the potential energy of the load in the hands, was capable of improved predictions of spinal compression forces. A stepwise polynomial equation was developed from EMG profiles of 15 muscles, and its spinal joint loading predictions at L4/L5 were compared to current methods of calculating spinal compression. Absolute muscle activation was shown to increase with increased loading height, indicating that the central nervous system responds to changes in spinal stability. The inclusion of potential energy into the calculation of spinal disc compression at L4/L5 improved estimates of the compressive forces acting on the spine. This is the first model to incorporate potential energy into a predictive model for lumbar spine compression without the use of electromyography. It was concluded that potential energy plays a vital role in dictating the recruitment patterns of the trunk.

Low back injury risk during repositioning of patients in bed: the influence of handling technique, patient weight and disability

The objective of the study was to investigate the low back load during repositioning of patients in bed and to assess the influence of patient's weight and disability. Nine female health care workers (HCWs) carried out six patient-handling tasks with different patient weight (59 ± 1, 83 ± 2 and 110 ± 4 kg) and handicap (hemiplegia, paraplegia and near-paralysis). The tasks were performed with optional use of simple, low-tech assistant devices (draw and sliding sheets). Peak low back compression exceeded the National Institute for Occupational Safety and Health action level of 3400 N in 25% of all trials (418). The influence of the HCW, i.e. the technique and assistive devices used, was higher than the effect of weight and disability in all tasks studied. ANOVA showed that on average for the six tasks 37%, 10% and 6% of the variance in low back loading was caused by variation in the factors HCW, patient's weight and disability, respectively. The result of this study is relevant for HCWs. It is shown that the repositioning technique and use of friction-reducing devices have higher influence on the low back load of the HCW than the patient's weight and disability.

Transfer of the horizontal patient: The effect of a friction reducing assistive device on low back mechanics

Recognizing that the transfer of bedridden patients is associated with a high rate of low back injuries, various devices have been developed to assist with sparing the patient handlers. The purpose of this study was to quantify the friction-reducing ability of three different ‘sliding’ patient transfer devices together with the subsequent consequences on the low back loads of people performing the transfers. Coefficients of friction of the devices were determined by ‘transferring’ a standard object and a ‘patient’ over several surfaces common to a hospital setting. Then three participants performed controlled transfers with the various devices. Electromyography to measure muscle activation levels together with external forces and kinematic positional data were collected during push, pull and twist transfers. Spine loads were estimated with a three-dimensional biomechanical static link-segment model of the human body. Simply sliding a patient on a cotton sheet (control condition) produced a coefficient of friction of 0.45. The assistive devices substantially reduced friction by well over one-half (coefficients of 0.18 – 0.21). However, when using the devices the subjects adopted a variety of postures and techniques, such that there were no consistent influences on trunk inclination, low back compression or muscle activation profiles. Direct measurement of reduced friction between the bed and the patient with a friction-reducing device together with measurement of the back loads when actually transferring a patient formed a proof of principle. Specifically, while the device lowers friction, the transfer technique adopted by the lifter must be proper to reduce low back loading and any subsequent risks of back troubles associated with patient transfers. The direction of hand forces and torso position remains important.

Comparison of instantaneous and cumulative loads on the low back and neck in orthodontists

Background. Musculoskeletal disorders of back and neck among orthodontists are prevalent. Due to low instantaneous load they have not been investigated. The present study aimed to quantify and compare instantaneous and cumulative loads on low back and neck in orthodontists. Methods. The sample included nine graduate orthodontic students from the University of Alberta and one practicing orthodontist to validate the generalization from student to professional group. The subjects were videotaped performing regular duties and the recorded postures were printed for biomechanical analysis of compression and shear loads and exposure time. Instantaneous loads were calculated using a biomechanical model developed specifically for this study and cumulative loads were calculated from the resultant loads. Findings. The average instantaneous low back compression loads for men and women were found to be 1383 N and 936 N respectively. The average daily cumulative load on the other hand were found to be 16.2 MN s and 9.9 MN s for males and females respectively. Interpretation. The study demonstrates that smaller loads cannot be ignored due to their magnitude if their duration is long because the time dependent properties of the tissues become modulating factor. Thus the measurement of instantaneous loads on tasks in orthodontists is not indicative of the amount of cumulative stress experienced by them.

Study of Workability and Safety Using Virtual Human Model

Lifting work is frequently observed in the production site of shipbuilding companies. It seems to be the work in which the body burden is bigger, and it often causes low back pain and injury of knee for aged shipbuilding workers. The low back pain concerns the compressive force on intervertebral disks, while the injury of knee concerns torque on the joint of knee. The analysis of such force and torque during the lifting job can be carried out using the biomechanical analysis, however, the calculation is usually complex and needs special know-how. Hence, the neural network method was applied in this paper to obtain the low back compression force (force on intervertebral disks) and torque on knee by developing C language program. The original teaching data were provided by the simulation using general-purpose software “Jack” applying virtual human model, and the neural network model learned these teaching data. Then, it was compared with the analytical results of “Jack” for the low back compression force and torque on knee, and both data obtained from the neural network and “Jack” were well coincided. Hence, the low back compression force and torque on knee at lifting work can be approximately gained by this neural network model without applying human software “Jack”.

Determining the minimum sampling rate needed to accurately quantify cumulative spine loading from digitized video

Cumulative low back loads have been linked to the reporting of low back pain. Traditional video-based methods used to estimate these loads are time intensive for data collection and analysis. Sampling less frequently would help to reduce the associated time and cost of this type of approach. The purpose of this study was to determine how the error in estimated cumulative low back loads is affected by reducing video sampling rate. Ten healthy male university students performed three laboratory, sagittal plane lifts of varying mass (2.3, 8.8, and 15.9 kg), speed (0.2, 0.4, 0.8 m/s), and postural demand (lift from floor to table; lower from shelf to table; lift from floor over barrier and lower to floor) while being videotaped (60 frames/s). Digitized body coordinates and anthropometrics were input into a static biomechanical model, resulting in estimates of low back compression and shear forces, and moment. Load-time histories for each condition underwent rectangular integration at 60 (gold standard), 30, 20, 15, 12, 10, 6, 5, 4, 3, 2 and 1 frames/s, resulting in estimates of low back cumulative loads. Mean relative errors with respect to 60 frames/s for all cumulative loads and all conditions were found to be below 8% at 1 frame/s, and less than 3% at 2 frames/s. In addition, analyses at sampling rates above 3 frames/s were not significantly different than the cumulative loads determined at 60 frames/s, for all conditions. The accuracy of cumulative loads exhibited even at low sampling rates can be attributed, in part, to the fact that overestimations and underestimations of the integrated loads tend to cancel out over the length of the tasks considered.

Study of Workability and Safety Using Virtual Human Model

Though the productivity, the quality, and the safety are three principles on any production, the safety seems to go after other two-productivity and quality, which are well-defined and have been studied theoretically and practically in the shipbuilding field. The safety is somehow vague and ill-defined, because it mainly depends on the human factor. However, Japanese shipyards have been full of the elder people, and are liable for keeping the safety and health to them.In this paper, the accidents in Japanese shipyards are reviewed and it is concluded that the accidents of falling and tumbling have occurred frequently : falling from the higher place and also tumbling down the stair. Then, these accidents are picked up, and the human task simulation was carried out using a virtual human model based on biomechanics and ergonomics ; the static strength prediction on human body and the low back compression analysis.As a result, it was understood that the torque on the ankle became greater at the work on the higher position and also on the vertical ladder, and the optimal inclined angle of the ladder was approximately 75 degree.

Assessment of an EMG-based method for continuous estimates of low back compression during asymmetrical occupational tasks

Variables, such as peak and accumulated moments and spine compression forces, have been shown to be risk factors for occupational low back pain. Estimates of these forces during prolonged, dynamic, asymmetric tasks using biomechanical models is complex and time-consuming. A simple technique for continuous measurement of these variables over a prolonged period is needed to measure the distribution of spinal loading during both sagittal plane lifts and complex asymmetrical jobs. The aim of this study was to determine whether a linear normalization of erector spinae EMG to spine compression force, called compression normalized EMG (CNEMG), could be used to estimate spinal loading for simulations of asymmetrical occupational tasks. The estimates of spine compression force obtained using the normalized EMG are presented in the form of an amplitude probability distribution function and are compared with estimates of a three-dimensional biomechanical model. The per cent time a worker spends above particular levels of spinal loading of interest, such as the NIOSH action limit for compression, are displayed. Five males performed simulated occupational tasks. The exposure time at a specific level of spine compression force for a combination of three tasks, estimated by CNEMG, was, on average, within 6.5% of the time calculated by the biomechanical model. However, if the task combination was dominated by an axial twisting moment, then the difference was, on average, 13.4%. The difference in magnitude of spine compression at a specific probability was, on average, 14.9% and when axial trunk twist dominated, 30.7%. It is concluded that CNEMG can estimate probability at a specific level of spine compression force when the task combination is characterized by a predominant extensor moment in the sagittal plane. Estimates of spine compression at a specific probability, and estimates obtained during task combinations dominated by an axial twisting moment, are poor.

Manual lifting task risk evaluation using computer vision system

Low back injury has been a significant problem in industry. Studies indicate that inappropriate design of manual material handling (mmh) task is one of the major factors causing low back pain. Here, an automated system of evaluating the possible risk of low back injury in mmh task is developed. The system applies computer vision technique to identify the working posture, then incorporating biomechanical model and anthropometric data to calculate the low back compression force. By comparing with the specified standard limits, the system can indicate the risk level of the task. Some recommendations will then be provided. The system has been validated by comparing with the existing 2-D software, and it is found to be valid and effecient.

A simple polynomial that predicts low-back compression during complex 3-D tasks.

While most existing models that predict loads on the low back for occupational risk analysis are restricted to assessing moments in the sagittal plan, a few have the ability to determine spine compression from three-dimensional (3-D) loading. The objective of this work was to find a method to estimate low-back compression forces during 3-D loading tasks from a model that contains as much biological content validity as the authors could incorporate, such as the effects of muscle co-contraction, but was simple enough to be implemented into a model appropriate for industrial use. The problem that had to be solved was how to represent the anatomical reality that a given muscle force vector contributes simultaneously to all three moments, flexion or extension, lateral bend and axial twist. Simply summing the compression components of independent equivalent muscles in each plane unrealistically assumes that muscles are uncoupled (i.e. each one works independently to support only one moment). In this study, loads in the various tissues of the low back that resulted from the simultaneous generation of moments about the three orthopaedic axes during 3-D tasks were estimated by an anatomically detailed 90 muscle model. A four-dimensional regression equation was developed to predict low-back compression from the three moments generated about the three axes (R2 = 0.94). Comparison of compression estimates from an uncoupled model showed that accounting for muscle coupling reduces compression by 22% on average. The predictive equation is presented to simplify analysis of complex 3-D industrial tasks for those who would like to incorporate it into their own models that produce moments of force in three plans of the L4/L5 level of the lumbar spine.